This pilot project will demonstrate the utility of cDNA microarrays for characterizing gene expression induced by PM2.5 (airborne particulate matter, aerodynamic diameter < 2.5 m) from urban indoor environments. The advent of microarray technology now permits rapid and simultaneous observation of expression patterns for thousands of genes throughout a genome. At the same time, the development at HSPH of the high-volume low-cutoff cascade impactor (HVCI) now permits sufficient PM2.5 mass to be collected for cell culture studies. Combining the HVCI's high mass recovery with the microarray's comprehensive view into the genome will permit the routine assessment of biologic activity in PM2.5. This capability would greatly elucidate the role of PM2.5 exposure for a variety of biological effects, such as genotoxicity and inflammatory response. Moreover, this approach is consistent with the understanding that PM2.5 is essentially a biologic agent, but an agent whose activity is likely to vary over time and location because of fluctuating environmental conditions. The specific aims for this two-year project are: a) utilize cDNA microarrays comprising ~33,000 human genes to quantity gene expression induced by organic-phase extracts from indoor PM2.5 collected within the HVAC system of a mixed-use building in Boston, MA; b) utilize bioinformatic techniques to identify groups of co-expressed genes, including those associated with regulatory pathways for genotoxic stress response, apoptosis, DNA repair, and receptor-dependent responses, such as for the Ah receptor; c) correlate gene expression patterns with the season that the PM2.5 was collected, concentrations of particle-bound carcinogenic pollutants in the organic-phase of PM2.5, and HVAC operating parameters. To achieve this proposal in a timely and cost-effective manner, an interdisciplinary collaboration has been established among the expertise in exposure assessment and tissue culture at the HSPH Kresge Center for Environmental Health, in bioinformatics in our Department of Biostatistics, and in microarray technology at the Harvard Center for Genomics Research.